Synthesis, structure and photoluminescence of (HgCl3)n (C6NO2H6)n(C6NO2H5)n•nH2O

A new isonicotinic acid compound with infinite mercury halide anionic chains, (HgCl3)n (C6NO2H6)n(C6NO2H5)n•nH2O (1), was obtained from the hydrothermal reaction and structurally characterized by X-ray single diffraction. The title compound is characteristic of a one-dimensional structure, based on one-dimensional (HgCl3)- anionic chains, protonated isonicotinic acid, neutral isonicotinic acid molecules and lattice water molecules. The protonated isonicotinic acid, neutral isonicotinic acid molecules and lattice water molecules are interconnected via hydrogen bonds to form a three-dimensional supramolecular framework. The (HgCl3)- anionic chains are anchored in the voids of the supramolecular framework via hydrogen bonds. Photoluminescent investigation reveals that the title compound displays a strong emission in blue region. The emission band is identified as the π-π* transitions of the isonicotinic acid moieties.KEY WORDS: Crystal, Isonicotinic, Halide, Mercury, Photoluminescence  Bull. Chem. Soc. Ethiop. 2011, 25(2), 233-238

Prediction of stroke risk in patients with transient ischemic attack: ABCD score and its derived scores

Transient Ischemic Attack (TIA) is a high-risk signal of acute ischemic cerebrovascular disease, indicates a significant increase in the risk of ischemic stroke, especially within 7 days. Risk assessment and stratification are important in patient with TIA. A variety of simple prediction scales were developed based on the risk factors for stroke in patients with TIA, such as the California scale, ABCD scale, and ABCD2 scale. Among them, the ABCD scale score is used most commonly, but as its application becomes more and more common, the defects of this scale are also increasingly apparent. In recent years, some derived scales of ABCD score were introduced in order to improve the sensitivity and specificity of prediction. This article reviews the evolution, contents, characteristics, and predictive value of the ABCD score and its derived scales in the prediction of the stroke risk in patients with TIA

A Study on the Vehicle Routing Problem Considering Infeasible Routing Based on the Improved Genetic Algorithm

The study aims to optimize the vehicle routing problem, considering infeasible routing, to minimize losses for the company. Firstly, a vehicle routing model with hard time windows and infeasible route constraints is established, considering both the minimization of total vehicle travel distance and the maximization of customer satisfaction. Subsequently, a Floyd-based improved genetic algorithm that incorporates local search is designed. Finally, the computational experiment demonstrates that compared with the classic genetic algorithm, the improved genetic algorithm reduced the average travel distance by 20.6% when focusing on travel distance and 18.4% when prioritizing customer satisfaction. In both scenarios, there was also a reduction of one in the average number of vehicles used. The proposed method effectively addresses the model introduced in this study, resulting in a reduction in total distance and an enhancement of customer satisfaction